Scenario simulations of ecosystems and their services require the climate data mostly from the Global Climate Models (GCMs). Because of most GCM simulated data with the coarse resolution (about 200-500 km), it is difficult to use these data to assess impacts of temperature change on various ecosystems on regional and local scales, although the data can be used to effectively predict the future temperature change on a global scale. To address the above issue, the downscaling model of mean temperature is developed with the spatial statistical method in this paper, combined with series data of DEM, latitude and longitude. For validating the downscaling model, the mean annual temperature is simulated under the three scenarios of HadCM3 A1Fi, A2a and B2a during the periods T1 (1961~1990), T2 (2010~2039), T3 (2040~2069), and T4 (2070~2099). In the simulation process, the data resolution is downscaled from 3.75°×0.125° to 1 km×1 km by High Accuracy Modeling (HASM). Simulation results show that mean temperature would continue to increase in the future 100 years under the three scenarios of HadCM3 (A1Fi, A2a and B2a). During the periods from T1 to T4, the rising rates of mean annual temperature are the greatest under scenario A1Fi, the average levels under scenario A2a, and the lowest under scenario B2a, which might increase per decade by 0.29℃, 0.23℃, and 0.17℃, respectively. Furthermore, mean annual temperature would have a changing trend of accelerated increase under scenarios A1Fi and A2a, but the increasing trend would be slow under scenario B2a in the next 100 years. The results show that the temperature data with IPCC GCM's coarse resolution can be effectively downscaled to high-resolution temperature data that could be used to assess the ecosystems and their services on the regional and local scales.
FAN Ze-meng, YUE Tian-xiang, CHEN Chuan-fa, SUN Xiao-fang
. Downscaling simulation of the temperature scenarios in China[J]. GEOGRAPHICAL RESEARCH, 2011
, 30(11)
: 2043
-2051
.
DOI: 10.11821/yj2011110010
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